BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment
Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering in-vitro and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of s...
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Veröffentlicht in: | Scientific reports 2016-07, Vol.6 (1), p.30330, Article 30330 |
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creator | Boel, Annekatrien Steyaert, Woutert De Rocker, Nina Menten, Björn Callewaert, Bert De Paepe, Anne Coucke, Paul Willaert, Andy |
description | Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering
in-vitro
and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from http://. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome. |
doi_str_mv | 10.1038/srep30330 |
format | Article |
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in-vitro
and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from http://. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome.</description><identifier>ISSN: 2045-2322</identifier><identifier>EISSN: 2045-2322</identifier><identifier>DOI: 10.1038/srep30330</identifier><identifier>PMID: 27461955</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>38/70 ; 631/114/2163 ; 631/1647/1511 ; 64/116 ; Animals ; CRISPR-Cas Systems ; Gene Editing - methods ; High-Throughput Nucleotide Sequencing - methods ; Humanities and Social Sciences ; INDEL Mutation ; multidisciplinary ; Science ; Sequence Analysis, DNA - methods ; Software ; Zebrafish ; Zebrafish Proteins - genetics</subject><ispartof>Scientific reports, 2016-07, Vol.6 (1), p.30330, Article 30330</ispartof><rights>The Author(s) 2016</rights><rights>Copyright © 2016, Macmillan Publishers Limited 2016 Macmillan Publishers Limited</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-52a1c4f7866a548833169c3f672095ab60a00cf1e673c10cff7ada5f375bc8e83</citedby><cites>FETCH-LOGICAL-c476t-52a1c4f7866a548833169c3f672095ab60a00cf1e673c10cff7ada5f375bc8e83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962088/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4962088/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,27924,27925,41120,42189,51576,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27461955$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Boel, Annekatrien</creatorcontrib><creatorcontrib>Steyaert, Woutert</creatorcontrib><creatorcontrib>De Rocker, Nina</creatorcontrib><creatorcontrib>Menten, Björn</creatorcontrib><creatorcontrib>Callewaert, Bert</creatorcontrib><creatorcontrib>De Paepe, Anne</creatorcontrib><creatorcontrib>Coucke, Paul</creatorcontrib><creatorcontrib>Willaert, Andy</creatorcontrib><title>BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment</title><title>Scientific reports</title><addtitle>Sci Rep</addtitle><addtitle>Sci Rep</addtitle><description>Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering
in-vitro
and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from http://. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome.</description><subject>38/70</subject><subject>631/114/2163</subject><subject>631/1647/1511</subject><subject>64/116</subject><subject>Animals</subject><subject>CRISPR-Cas Systems</subject><subject>Gene Editing - methods</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Humanities and Social Sciences</subject><subject>INDEL Mutation</subject><subject>multidisciplinary</subject><subject>Science</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Software</subject><subject>Zebrafish</subject><subject>Zebrafish Proteins - genetics</subject><issn>2045-2322</issn><issn>2045-2322</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>EIF</sourceid><recordid>eNptkE9LAzEQxYMottQe_AKSq8Jq_myyux6EttQqFD2oB0_LNJtst7RJTbZiv727VEsF5zLDzJv34IfQOSXXlPD0Jni95oRzcoS6jMQiYpyx44O5g_ohLEhTgmUxzU5RhyWxpJkQXfQ-HLyOHqLJ-BYPoVZzDBaW21AF7Ax-0l91NNFWe6grZ_GL_thoqypb4gJqwMZ5XGrrVhrroqrbPYSgQ1hpW5-hEwPLoPs_vYfe7sdt1vR58jgaTCMVJ7KOBAOqYpOkUoKI05RzKjPFjUwYyQTMJAFClKFaJlzRZjIJFCAMT8RMpTrlPXS3811vZitdqCbawzJf-2oFfps7qPK_F1vN89J95nEmGUlbg8udgfIuNDTN_peSvEWc7xE32ovDsL3yF2gjuNoJQnOypfb5wm18wzT84_YNg4-GMg</recordid><startdate>20160727</startdate><enddate>20160727</enddate><creator>Boel, Annekatrien</creator><creator>Steyaert, Woutert</creator><creator>De Rocker, Nina</creator><creator>Menten, Björn</creator><creator>Callewaert, Bert</creator><creator>De Paepe, Anne</creator><creator>Coucke, Paul</creator><creator>Willaert, Andy</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>C6C</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope></search><sort><creationdate>20160727</creationdate><title>BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment</title><author>Boel, Annekatrien ; Steyaert, Woutert ; De Rocker, Nina ; Menten, Björn ; Callewaert, Bert ; De Paepe, Anne ; Coucke, Paul ; Willaert, Andy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c476t-52a1c4f7866a548833169c3f672095ab60a00cf1e673c10cff7ada5f375bc8e83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>38/70</topic><topic>631/114/2163</topic><topic>631/1647/1511</topic><topic>64/116</topic><topic>Animals</topic><topic>CRISPR-Cas Systems</topic><topic>Gene Editing - methods</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Humanities and Social Sciences</topic><topic>INDEL Mutation</topic><topic>multidisciplinary</topic><topic>Science</topic><topic>Sequence Analysis, DNA - methods</topic><topic>Software</topic><topic>Zebrafish</topic><topic>Zebrafish Proteins - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boel, Annekatrien</creatorcontrib><creatorcontrib>Steyaert, Woutert</creatorcontrib><creatorcontrib>De Rocker, Nina</creatorcontrib><creatorcontrib>Menten, Björn</creatorcontrib><creatorcontrib>Callewaert, Bert</creatorcontrib><creatorcontrib>De Paepe, Anne</creatorcontrib><creatorcontrib>Coucke, Paul</creatorcontrib><creatorcontrib>Willaert, Andy</creatorcontrib><collection>SpringerOpen</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Scientific reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Boel, Annekatrien</au><au>Steyaert, Woutert</au><au>De Rocker, Nina</au><au>Menten, Björn</au><au>Callewaert, Bert</au><au>De Paepe, Anne</au><au>Coucke, Paul</au><au>Willaert, Andy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment</atitle><jtitle>Scientific reports</jtitle><stitle>Sci Rep</stitle><addtitle>Sci Rep</addtitle><date>2016-07-27</date><risdate>2016</risdate><volume>6</volume><issue>1</issue><spage>30330</spage><pages>30330-</pages><artnum>30330</artnum><issn>2045-2322</issn><eissn>2045-2322</eissn><abstract>Targeted mutagenesis by the CRISPR/Cas9 system is currently revolutionizing genetics. The ease of this technique has enabled genome engineering
in-vitro
and in a range of model organisms and has pushed experimental dimensions to unprecedented proportions. Due to its tremendous progress in terms of speed, read length, throughput and cost, Next-Generation Sequencing (NGS) has been increasingly used for the analysis of CRISPR/Cas9 genome editing experiments. However, the current tools for genome editing assessment lack flexibility and fall short in the analysis of large amounts of NGS data. Therefore, we designed BATCH-GE, an easy-to-use bioinformatics tool for batch analysis of NGS-generated genome editing data, available from http://. BATCH-GE detects and reports indel mutations and other precise genome editing events and calculates the corresponding mutagenesis efficiencies for a large number of samples in parallel. Furthermore, this new tool provides flexibility by allowing the user to adapt a number of input variables. The performance of BATCH-GE was evaluated in two genome editing experiments, aiming to generate knock-out and knock-in zebrafish mutants. This tool will not only contribute to the evaluation of CRISPR/Cas9-based experiments, but will be of use in any genome editing experiment and has the ability to analyze data from every organism with a sequenced genome.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>27461955</pmid><doi>10.1038/srep30330</doi><oa>free_for_read</oa></addata></record> |
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subjects | 38/70 631/114/2163 631/1647/1511 64/116 Animals CRISPR-Cas Systems Gene Editing - methods High-Throughput Nucleotide Sequencing - methods Humanities and Social Sciences INDEL Mutation multidisciplinary Science Sequence Analysis, DNA - methods Software Zebrafish Zebrafish Proteins - genetics |
title | BATCH-GE: Batch analysis of Next-Generation Sequencing data for genome editing assessment |
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